1 Gross Domestic Product (GDP)

We can initially approach the concept of GDP by explaining the terms “Product”, “Domestic” and “Gross” separately (Lequiller and Blades 2014, Chapter 1):

Product: refers to what we are trying to measure, which is the production of goods and services, with no double counting, in a given period, \(t\) and carried out by:
- Profit-making enterprises (economists use the alternative term firms)
- Non-profit institutions
- Goverment bodies
- Households
“Domestic”: indicates that the production to be taken into account is the one that is carried within a certain geographical territory, \(s\), clearly delimited.
- In that sense if we use the concept of of GDP we don’t care who carried out the production in \(t\) but only where the production was carried out in \(t\)
“Gross”: it means that depreciation or the cost of using capital is not deducted (in the field of economics it is called consumption of fixed capital).
- In other words, the decrease in the value of the assets due to physical deterioration, foreseeable wear or accidental damage is not deducted.
- Why depreciation or the cost of using capital is not deducted?
  - It is a variable difficult to measure and the methods used to measure it tend to differ between countries creating problems for international comparison

1.1 Three equivalent ways to measure the GDP

Initially the units in which GDP is measure is in monetary units of a specific currency, \(c\). Therefore \(GDP_{s}^{c}(t)\) means the \(GDP\) of territory \(s\) in a given period \(t\). To make the discussion less abstract we present a plot of \(GDP\) for Colombia, \(s = COL\), expressed in Colombian pesos, \(c = COP\), for the years 1960 to 2019, \(t = 1960, \ldots, 2019\):

# Clean data
gdp_colombia <- wbstats::wb(country   = "COL", 
                             indicator = "NY.GDP.MKTP.CN", 
                             startdate = 1960, 
                             enddate   = 2019) %>% 
    tibble::as_tibble() %>% 
    dplyr::select(date, value) %>%
    dplyr::mutate(date       = as.double(date),
                  label_text = stringr::str_glue('Year: {date}
                                                  GDP: {value %>% scales::dollar()}')) 

# Plot
    
static_plot <- gdp_colombia %>%
    # Data
    ggplot2::ggplot(aes(x = date, y =value)) +
    # Geoms
    ggplot2::geom_point(aes(text = label_text),
                        shape = 21, 
                        color = "black", 
                        fill  = "red") + 
    ggplot2::geom_line(linetype = "dashed") +
    # Scales
    scale_x_continuous(breaks = c(1960:2019)) +
    scale_y_continuous(breaks = seq(from = 0, to = 1.10e15, by = 1e14), 
                       labels = scales::number_format(scale = 1/1e12, suffix = "B")) +
    labs(x = "Year",
         y = "GDP in current local currency [B = Billion in long scale (10^12)]",
         title = "GDP of Colombia: 1960-2019") +
    # Themes
    theme(panel.border      = element_rect(fill = NA, color = "black"),
          plot.background   = element_rect(fill = "#f3fcfc"),          
          panel.background  = element_rect(fill = "#f3f7fc"),
          legend.background = element_rect(fill = "#f3fcfc"), 
          plot.title        = element_text(face = "bold"),
          axis.text.x=element_text(angle = -90, vjust = 0.5),
          axis.title        = element_text(face = "bold"),
          legend.title      = element_text(face = "bold"),
          axis.text         = element_text(face = "bold"))

    # Interactivity
    static_plot %>% 
      plotly::ggplotly(tooltip = "text")

Economic concepts

Luis Francisco Gomez Lopez

2020-07-13

1 Gross Domestic Product (GDP)

1.1 Three equivalent ways to measure the GDP

Bibliography